Seed1,3 Analysis
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Graph_Attributes<-data.table::fread(here::here("data", "CGCS-GraphData-NodeTypes.csv"))
s1 <- data.table::fread(here::here("dataQ2","dfSeed1Reduced.csv"))
s3 <- data.table::fread(here::here("dataQ2","dfSeed3Reduced.csv"))
s1_network <- subset(s1, select = c(Source, Target, Weight))
s3_network <- subset(s3, select = c(Source, Target, Weight))
s1_edgelist <- s1_network
s1_graph <- graph.data.frame(s1_edgelist, directed = TRUE)
s3_edgelist <- s3_network
s3_graph <- graph.data.frame(s3_edgelist, directed = TRUE)
s1_graph2<-igraph::simplify(s1_graph, remove.multiple = FALSE, remove.loops = TRUE)
s3_graph2<-igraph::simplify(s3_graph, remove.multiple = FALSE, remove.loops = TRUE)
tail(s1, 10)## V1 Source eType Target Time Weight SourceLocation
## 1: 2551 481408 6 561157 17712000 4 3
## 2: 834 626174 6 561157 23155200 1 3
## 3: 2675 462691 6 561157 24019200 6 3
## 4: 2548 481408 6 509607 11836800 4 3
## 5: 147 552243 6 509607 20995200 0 3
## 6: 2596 594696 6 509607 31363200 5 3
## 7: 3011 564784 2 547205 22653139 4 NA
## 8: 5053 583737 3 547205 22653139 4 NA
## 9: 3010 564784 2 547205 19623898 80 NA
## 10: 4940 583737 3 547205 19623898 80 NAunique(Graph_Attributes$NodeType)## [1] 1 4 3 2 5s1_edgelist <- s1_edgelist[!duplicated(s1_edgelist)]S1:
## + 83/83 vertices, named, from 38d1848:
## [1] 600971 564804 626174 470784 554368 638591 477333 533691 558444 490882
## [11] 594696 462691 631159 605385 506539 564784 466429 532462 583737 631490
## [21] 510031 552988 575811 547483 474123 481408 620120 493846 469603 542731
## [31] 573191 537659 527214 603212 521273 597450 591024 643930 479674 495487
## [41] 573678 589043 584511 552243 501914 536173 630700 529018 571938 579269
## [51] 536346 520660 567195 527449 459381 595298 466907 589943 577992 537281
## [61] 523927 580426 642329 503701 644226 632961 473173 630626 616315 575030
## [71] 621924 503218 571970 640784 595581 606730 499467 616453 625756 657173
## [81] 561157 509607 547205## [1] 793
Vis Network:
Sources <- s1 %>%
distinct(Source) %>%
rename(label = Source)
Targets <- s1 %>%
distinct(Target) %>%
rename(label = Target)
# Creating a Node List:
nodes <- full_join(Sources, Targets, by = "label")
nodes## label
## 1 600971
## 2 564804
## 3 626174
## 4 470784
## 5 554368
## 6 638591
## 7 477333
## 8 533691
## 9 558444
## 10 490882
## 11 594696
## 12 462691
## 13 631159
## 14 605385
## 15 506539
## 16 564784
## 17 466429
## 18 532462
## 19 583737
## 20 631490
## 21 510031
## 22 552988
## 23 575811
## 24 547483
## 25 474123
## 26 481408
## 27 620120
## 28 493846
## 29 469603
## 30 542731
## 31 573191
## 32 537659
## 33 527214
## 34 603212
## 35 521273
## 36 597450
## 37 591024
## 38 643930
## 39 479674
## 40 495487
## 41 573678
## 42 589043
## 43 584511
## 44 552243
## 45 501914
## 46 536173
## 47 630700
## 48 529018
## 49 571938
## 50 579269
## 51 536346
## 52 520660
## 53 567195
## 54 527449
## 55 459381
## 56 595298
## 57 466907
## 58 589943
## 59 577992
## 60 537281
## 61 523927
## 62 580426
## 63 642329
## 64 503701
## 65 644226
## 66 632961
## 67 473173
## 68 630626
## 69 616315
## 70 575030
## 71 621924
## 72 503218
## 73 571970
## 74 640784
## 75 595581
## 76 606730
## 77 499467
## 78 616453
## 79 625756
## 80 657173
## 81 561157
## 82 509607
## 83 547205nodes <- nodes %>% rowid_to_column("id")
nodes## id label
## 1 1 600971
## 2 2 564804
## 3 3 626174
## 4 4 470784
## 5 5 554368
## 6 6 638591
## 7 7 477333
## 8 8 533691
## 9 9 558444
## 10 10 490882
## 11 11 594696
## 12 12 462691
## 13 13 631159
## 14 14 605385
## 15 15 506539
## 16 16 564784
## 17 17 466429
## 18 18 532462
## 19 19 583737
## 20 20 631490
## 21 21 510031
## 22 22 552988
## 23 23 575811
## 24 24 547483
## 25 25 474123
## 26 26 481408
## 27 27 620120
## 28 28 493846
## 29 29 469603
## 30 30 542731
## 31 31 573191
## 32 32 537659
## 33 33 527214
## 34 34 603212
## 35 35 521273
## 36 36 597450
## 37 37 591024
## 38 38 643930
## 39 39 479674
## 40 40 495487
## 41 41 573678
## 42 42 589043
## 43 43 584511
## 44 44 552243
## 45 45 501914
## 46 46 536173
## 47 47 630700
## 48 48 529018
## 49 49 571938
## 50 50 579269
## 51 51 536346
## 52 52 520660
## 53 53 567195
## 54 54 527449
## 55 55 459381
## 56 56 595298
## 57 57 466907
## 58 58 589943
## 59 59 577992
## 60 60 537281
## 61 61 523927
## 62 62 580426
## 63 63 642329
## 64 64 503701
## 65 65 644226
## 66 66 632961
## 67 67 473173
## 68 68 630626
## 69 69 616315
## 70 70 575030
## 71 71 621924
## 72 72 503218
## 73 73 571970
## 74 74 640784
## 75 75 595581
## 76 76 606730
## 77 77 499467
## 78 78 616453
## 79 79 625756
## 80 80 657173
## 81 81 561157
## 82 82 509607
## 83 83 547205# Creating an Edge List:
per_route <- s1 %>%
group_by(Source, Target) %>%
summarise(weight = n()) %>%
ungroup()
per_route## # A tibble: 788 x 3
## Source Target weight
## <int> <int> <int>
## 1 462691 459381 2
## 2 462691 466429 1
## 3 462691 466907 2
## 4 462691 470784 1
## 5 462691 473173 2
## 6 462691 503701 2
## 7 462691 523927 2
## 8 462691 527449 2
## 9 462691 536346 2
## 10 462691 537281 2
## # ... with 778 more rowsedges <- per_route %>%
left_join(nodes, by = c("Source" = "label")) %>%
rename(from = id)
edges <- edges %>%
left_join(nodes, by = c("Target" = "label")) %>%
rename(to = id)
edges <- select(edges, from, to, weight)
edges## # A tibble: 788 x 3
## from to weight
## <int> <int> <int>
## 1 12 55 2
## 2 12 17 1
## 3 12 57 2
## 4 12 4 1
## 5 12 67 2
## 6 12 64 2
## 7 12 61 2
## 8 12 54 2
## 9 12 51 2
## 10 12 60 2
## # ... with 778 more rows# Creating a Network:
routes_network <- network(edges, vertex.attr = nodes, matrix.type = "edgelist", ignore.eval = FALSE)
class(routes_network)## [1] "network"routes_network## Network attributes:
## vertices = 83
## directed = TRUE
## hyper = FALSE
## loops = FALSE
## multiple = FALSE
## bipartite = FALSE
## total edges= 788
## missing edges= 0
## non-missing edges= 788
##
## Vertex attribute names:
## id label vertex.names
##
## Edge attribute names:
## weightplot(routes_network, vertex.cex = 3, main = "Seed-1 Graph")